Skip to main content
Glama

get_transcript

Read-only

Extract the full transcript from a YouTube video to summarize content or answer questions about what was said.

Instructions

Extract the full transcript/captions from a YouTube video. Use this to understand video content, summarize videos, or answer questions about what was said. COMBINE WITH: get_video_frames for visual context, search_in_transcript to find specific moments, or get_video_info for metadata. TIP: Use list_caption_languages first to check available languages. Note: Only works for videos with captions enabled.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoIdYesYouTube video ID or URL
languageNoLanguage code (e.g., en, es, fr)en
withTimestampsNoInclude timestamps for each segment
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it's a safe read operation. The description adds useful behavioral context: only works for videos with captions enabled and suggests checking available languages. However, it doesn't specify error behavior for missing captions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Five sentences with clear structure: action statement, use cases, combination suggestions, tip, and note. Every sentence adds value without redundancy. Information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description should explain return format. It mentions 'full transcript/captions' but doesn't describe structure (plain text, segments with timestamps). Error handling (e.g., no captions) is incomplete. Sibling count is high, so missing details reduce completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema documentation covers 100% of parameters. The description adds value beyond schema by advising to use list_caption_languages first for language selection and implying timestamps are per-segment. This extra guidance justifies above the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it extracts full transcript/captions from YouTube videos. It distinguishes from siblings by mentioning combination with other tools (get_video_frames, search_in_transcript) and suggests using list_caption_languages first. The verb 'Extract' and resource 'transcript/captions' are specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description explicitly says when to use: to understand video content, summarize, or answer questions. It provides context on combining with sibling tools for different needs. The note about only working with captions enabled implies limitations, but lacks explicit when-not or alternatives for non-caption cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ixex/tubepilot'

If you have feedback or need assistance with the MCP directory API, please join our Discord server